Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Using Discriminant Eigenfeatures for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical Discriminant Analysis for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Handbook of Face Recognition
Feature extraction approaches based on matrix pattern: MatPCA and MatFLDA
Pattern Recognition Letters
Editorial: Recent submissions in linear dimensionality reduction and face recognition
Pattern Recognition Letters
Rapid and brief communication: Face recognition based on 2D Fisherface approach
Pattern Recognition
(2D)2LDA: An efficient approach for face recognition
Pattern Recognition
Journal of Cognitive Neuroscience
Rapid and brief communications: A Fourier-LDA approach for image recognition
Pattern Recognition
2D-LDA: A statistical linear discriminant analysis for image matrix
Pattern Recognition Letters
Representing image matrices: eigenimages versus eigenvectors
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Image processing algorithms employing two-dimensional Karhunen-Loeve Transform
Annales UMCS, Informatica
2DLDA-based texture recognition in the aspect of objective image quality assessment
Annales UMCS, Informatica
Face recognition using two-dimensional CCA and PLS
International Journal of Biometrics
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Paper presents an efficient dimensionality reduction method for images (e.g. human faces databases). It does not require any usual pre-processing stage (like down-scaling or filtering). Its main advantage is associated with efficient representation of images leading to accurate recognition. Analysis is performed using two-dimensional Principal Component Analysis and Linear Discriminant Analysis and reduction by means of two-dimensional Karhunen-Loeve Transform. The paper presents mathematical principles together with some results of recognition experiments on popular facial databases. The experiments performed on several facial image databases (BioID [11], ORL/AT&T [3], FERET [8], Face94 [4] and Face95 [5]) showed that face recognition using this type of feature space dimensionality reduction is particularly convenient and efficient, giving high recognition performance.